AIMC Journal:
Journal of chemical information and modeling

Showing 291 to 300 of 934 articles

Biomolecular Adsorption on Nanomaterials: Combining Molecular Simulations with Machine Learning.

Journal of chemical information and modeling Apr 16, 2024
Adsorption free energies of 32 small biomolecules (amino acids side chains, fragments of lipids, and sugar molecules) on 33 different nanomaterials, computed by the molecular dynamics - metadynamics methodology, have been analyzed using statistical m...
Adsorption Machine Learning Neural Networks, Computer Amino Acids Algorithms Molecular Dynamics Simulation Nanostructures Thermodynamics
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ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein-DNA Interaction Hotspots.

Journal of chemical information and modeling Apr 8, 2024
Protein-DNA interactions are pivotal to various cellular processes. Precise identification of the hotspot residues for protein-DNA interactions holds great significance for revealing the intricate mechanisms in protein-DNA recognition and for providi...
Thermodynamics Support Vector Machine Proteins DNA DNA-Binding Proteins Algorithms Protein Binding Neural Networks, Computer Machine Learning
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Modeling Zinc Complexes Using Neural Networks.

Journal of chemical information and modeling Apr 8, 2024
Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build...
Zinc Models, Molecular Neural Networks, Computer Molecular Conformation Coordination Complexes Thermodynamics Molecular Dynamics Simulation Quantum Theory
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ALDELE: All-Purpose Deep Learning Toolkits for Predicting the Biocatalytic Activities of Enzymes.

Journal of chemical information and modeling Apr 4, 2024
Rapidly predicting enzyme properties for catalyzing specific substrates is essential for identifying potential enzymes for industrial transformations. The demand for sustainable production of valuable industry chemicals utilizing biological resources...
Enzymes Biocatalysis Protein Conformation Deep Learning Models, Molecular
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MolProphet: A One-Stop, General Purpose, and AI-Based Platform for the Early Stages of Drug Discovery.

Journal of chemical information and modeling Apr 2, 2024
Artificial intelligence (AI) is an effective tool to accelerate drug discovery and cut costs in discovery processes. Many successful AI applications are reported in the early stages of small molecule drug discovery. However, most of those application...
Drug Discovery Small Molecule Libraries Humans Artificial Intelligence Software
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Predicting Elimination of Small-Molecule Drug Half-Life in Pharmacokinetics Using Ensemble and Consensus Machine Learning Methods.

Journal of chemical information and modeling Apr 2, 2024
Half-life is a significant pharmacokinetic parameter included in the excretion phase of absorption, distribution, metabolism, and excretion. It is one of the key factors for the successful marketing of drug candidates. Therefore, predicting half-life...
Machine Learning Support Vector Machine Pharmacokinetics Quantitative Structure-Activity Relationship Small Molecule Libraries Pharmaceutical Preparations Half-Life
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HydraProt: A New Deep Learning Tool for Fast and Accurate Prediction of Water Molecule Positions for Protein Structures.

Journal of chemical information and modeling Mar 29, 2024
Water molecules are integral to the structural stability of proteins and vital for facilitating molecular interactions. However, accurately predicting their precise position around protein structures remains a significant challenge, making it a vibra...
Proteins Deep Learning Neural Networks, Computer Water Software
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Inference of Developmental Hierarchy and Functional States of Exhausted T Cells from Epigenetic Profiles with Deep Learning.

Journal of chemical information and modeling Mar 28, 2024
Exhausted T cells are a key component of immune cells that play a crucial role in the immune response against cancer and influence the efficacy of immunotherapy. Accurate assessment and measurement of T-cell exhaustion (TEX) are critical for understa...
Epigenesis, Genetic DNA Methylation Humans MicroRNAs Tumor Microenvironment Neoplasms Deep Learning T-Lymphocytes
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Sequential Contrastive and Deep Learning Models to Identify Selective Butyrylcholinesterase Inhibitors.

Journal of chemical information and modeling Mar 26, 2024
Butyrylcholinesterase (BChE) is a target of interest in late-stage Alzheimer's Disease (AD) where selective BChE inhibitors (BIs) may offer symptomatic treatment without the harsh side effects of acetylcholinesterase (AChE) inhibitors. In this study,...
Deep Learning Butyrylcholinesterase Humans Acetylcholinesterase Models, Molecular Alzheimer Disease Cholinesterase Inhibitors
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From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties.

Journal of chemical information and modeling Mar 26, 2024
A novel approach to the utilization of nuclear magnetic resonance (NMR) spectroscopy data in the prediction of logD through machine learning algorithms is shown. In the analysis, a data set of 754 chemical compounds, organized into 30 clusters, was e...
Machine Learning Algorithms Support Vector Machine Chemical Phenomena Artificial Intelligence Magnetic Resonance Spectroscopy
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